[R] Confidence Band for empirical distribution function

[Hotz, T.]

Dear Kjetil,

As I already mentioned, it appears that there isn't a function 
available calculating the quantiles directly (at least, it doesn't appear
in the C source of ctest). So as I already suggested, uniroot (or a similar
C routine which calls the corresponding C code directly) is probably the 
best you can do (apart from writing it completely yourself).

I didn't program this using uniroot, but I'd certainly try the following 
for speed-up:

- For symmetry reasons, you only need to compute half of the quantiles.
- The quantiles depend smoothly on the probabilities (of your reference
distribution). Therefore, calculating only a "few" for probabilities 
between 0 and 0.5, and using (e.g. linear) interpolation should be
satisfying.

I am sorry not be of more help.

HTH anyway

Thomas

> -----Original Message-----
> From: kjetil brinchmann halvorsen [mailto:kjetil at entelnet.bo]
> Sent: 23 July 2003 15:46
> To: Hotz, T.
> Subject: RE: [R] Confidence Band for empirical distribution function
> 
> 
> On 22 Jul 2003 at 11:37, Hotz, T. wrote:
> 
> > Dear Leif,
> > 
> > If you look at the definition of ks.test, you'll find the lines
> > 
> > pkstwo <- function(x, tol = 1e-06) {
> >     if (is.numeric(x)) 
> >         x <- as.vector(x)
> >     else stop("Argument x must be numeric")
> >     p <- rep(0, length(x))
> >     p[is.na(x)] <- NA
> >     IND <- which(!is.na(x) & (x > 0))
> >     if (length(IND) > 0) {
> >         p[IND] <- .C("pkstwo", as.integer(length(x)), p = 
> as.double(x[IND]), 
> >             as.double(tol), PACKAGE = "ctest")$p
> >     }
> >     return(p)
> > }
> > 
> > which calls C code to calculate the p-values given the test 
> statistic.
> > You'll find explanations on what this function does in the 
> original C file
> > src/library/ctest/src/ks.c
> > 
> > I haven't tried that but I assume that you could use it to 
> calculate p-values
> > given the test-statistics yourself.
> 
> That could certainly be done, but what was asked for is the inverse, 
> which can be calculated, using for instance uniroot(). I tried that, 
> but it is to slow, .C() will be called repeatedly in a loop. For me 
> it took several minutes.
> 
> Kjetil Halvorsen
> 
> > 
> > Please also note that ks.test() returns the p-value as well.
> > 
> > If you need quantiles, I assume you need to invert the cdf yourself,
> > e.g. using uniroot().
> > 
> > HTH
> > 
> > Thomas
> >       
> > ---
> > 
> > Thomas Hotz
> > Research Associate in Medical Statistics
> > University of Leicester
> > United Kingdom
> > 
> > Department of Epidemiology and Public Health
> > 22-28 Princess Road West
> > Leicester
> > LE1 6TP
> > Tel +44 116 252-5410
> > Fax +44 116 252-5423
> > 
> > Division of Medicine for the Elderly
> > Department of Medicine
> > The Glenfield Hospital
> > Leicester
> > LE3 9QP
> > Tel +44 116 256-3643
> > Fax +44 116 232-2976
> > 
> > 
> > > -----Original Message-----
> > > From: Leif.Boysen [mailto:boysen at math.uni-goettingen.de]
> > > Sent: 21 July 2003 14:42
> > > To: r-help at stat.math.ethz.ch
> > > Subject: [R] Confidence Band for empirical distribution function
> > > 
> > > 
> > > Hi,
> > > 
> > > I was trying to draw an empirical distribution function 
> with uniform
> > > confidence bands. So I tried to find a way to calculate 
> values of the
> > > Kolmogorov-Smirnov Distribution but failed.
> > > I guess it must be hidden somewhere (since the ks-test is 
> > > implemented),
> > > but I was unable to find it. 
> > > 
> > > Is there any way to do this?
> > > 
> > > Thanks
> > > 
> > > Leif Boysen
> > > 
> > > ______________________________________________
> > > R-help at stat.math.ethz.ch mailing list
> > > https://www.stat.math.ethz.ch/mailman/listinfo/r-help
> > >
> > 
> > ______________________________________________
> > R-help at stat.math.ethz.ch mailing list
> > https://www.stat.math.ethz.ch/mailman/listinfo/r-help
> 
> 
>